Impedance plethysmography as an alternative method for the diagnosis of peripheral arterial disease

Novel Peripheral Perfusion Dynamics Indices for Detecting and Grading Arterial Stenosis

PURPOSE

Peripheral artery disease causes severe morbidity, especially in diabetics and the elderly. There is a need for accurate noninvasive detection of peripheral arterial stenosis. The study has tested the hypothesis that arterial stenosis and the associated adaptation of the downstream circulation yield characteristic changes in the leg perfusion dynamics that enable early diagnosis, utilizing impedance plethysmography.

METHODS

The arterial perfusion dynamic was derived from impedance plethysmography (IPG). Two degrees of arterial stenosis were emulated by inflating a blood-pressure cuff around the thigh to 45 and 90 mmHg, in healthy volunteers (n = 30). IPG signals were acquired continuously throughout the experiment. Ankle and brachial blood pressures were measured at the beginning of each experiment and at the end of each emulated stenosis phase.

RESULTS

Thigh compressions did not affect the pulse-transit time, but prolonged the time to the peak perfusion wave. Segmentation of the perfusion upstroke into two phases, at the time point of maximum acceleration (MAT), revealed that arterial compression prolonged only the initial slow phase duration (SPd). The MAT and SPd were proportional to the emulated stenosis severity and detected the arterial stenosis with high sensitivity (> 93%) and specificity (100%). The SPd increased from 46.4 ± 21.2 ms at baseline to 75.4 ± 38.5 ms and 145 ± 39 ms under 45 mmHg and 90 mmHg compressions (p < 0.001), without affecting the pulse-transit time.

CONCLUSIONS

The novel method and indices can identify and grade the emulated arterial stenosis with high accuracy and may assist in differentiating between focal arterial stenosis and widespread arterial hardening.

Intelligent Oscillometric System for Automatic Detection of Peripheral Arterial Disease

Peripheral arterial disease (PAD) is a progressing arterial disorder that is associated with significant morbidity and mortality. The conventional PAD detection methods are invasive, cumbersome, or require expensive equipment and highly trained technicians. Here, we propose a new automated, noninvasive, and easy-to-use method for the detection of PAD based on characterizing the arterial system by applying an external varying pressure using a cuff. The superposition of the internal arterial pressure and the externally applied pressure were measured and mathematically modeled as a function of cuff pressure. A feature-based learning algorithm was then designed to identify PAD patterns by analyzing the parameters of the derived mathematical models. Genetic algorithm and principal component analysis were employed to select the best predictive features distinguishing PAD patterns from normal. A RUSBoost ensemble model using neural network as the base learner was designed to diagnose PAD from genetic algorithm selected features. The proposed method was validated on data collected from 14 PAD patients and 19 healthy individuals. It achieved a high accuracy, sensitivity, and specificity of 91.4%, 90.0%, and 92.1%, respectively, in detecting PAD. The effect of age, a confounding factor that may have impacted our analyzes, was not considered in this study. The proposed method shows promise toward noninvasive and accurate detection of PAD and can be integrated into routine oscillometric blood pressure measurements.

Modelling Dynamically Re-Sizeable Electrodes (DRE) for Targeted Transcutaneous Measurements in Impedance Plethysmography

Impedance plethysmography of extremities typically involves band electrodes around limbs to monitor changes in blood volume. This often causes monitored blood variations to only generate minuscule impedance values relative to the measured baseline, attributed to the tissue surrounding the artery or vein of interest. Smaller, ECG type electrodes can provide a larger signal, however their output is very easily affected by the placement of the electrodes relative to the targeted vasculature. This paper presents a novel method to adjust the active surface of electrodes, introducing Dynamically Re-sizeable Electrodes (DRE), to only target the exact area of interest, forming localised electrodes, without having to manually re-position them. Elongated rectangular electrodes were partitioned into smaller electrode segments, interconnected through custom circuitry. For the development and assessment of the DRE system, work was carried out both experimentally in-vitro on gelatine phantoms using custom switching circuits and through finite element modelling (FEM) simulations in COMSOL. A scanning sequence made use of DRE in single segment variable tetra-pole (SSVT) mode proved capable to identify the transcutaneous location of the blood vessel of interest and the specific electrode segments located in its vicinity. Impedance measurements were then taken using these segments connected to form localised electrodes only placed over the targeted vessel. The resulting localised electrodes exhibited up to [Formula: see text] increased sensitivity to blood variations relative to larger electrodes.

Peripheral vascular disease assessment in the lower limb: a review of current and emerging non-invasive diagnostic methods

BACKGROUND

Worldwide, at least 200 million people are affected by peripheral vascular diseases (PVDs), including peripheral arterial disease (PAD), chronic venous insufficiency (CVI) and deep vein thrombosis (DVT). The high prevalence and serious consequences of PVDs have led to the development of several diagnostic tools and clinical guidelines to assist timely diagnosis and patient management. Given the increasing number of diagnostic methods available, a comprehensive review of available technologies is timely in order to understand their limitations and direct future development effort.

MAIN BODY

This paper reviews the available diagnostic methods for PAD, CVI, and DVT with a focus on non-invasive modalities. Each method is critically evaluated in terms of sensitivity, specificity, accuracy, ease of use, procedure time duration, and training requirements where applicable.

CONCLUSION

This review emphasizes the limitations of existing methods, highlighting a latent need for the development of new non-invasive, efficient diagnostic methods. Some newly emerging technologies are identified, in particular wearable sensors, which demonstrate considerable potential to address the need for simple, cost-effective, accurate and timely diagnosis of PVDs.